• Journal of Navigation and Port Research
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• v.35 no.9
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• pp.707-715
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• 2011

To propose an ergonomic layout on the bridge, this study conducted a usability evaluation on the on-bridge navigational equipment of a college training ship that is in use at present. Through the usability evaluation on the training ship navigators, the possibility of operational errors with navigational equipment, the possibility of readout errors with display devices and even the effect of navigational equipment on navigation were evaluated beyond the scope of existing layouts, which adopt only the importance and usage frequency of navigational equipment. By taking ergonomic variables into consideration, this study suggested an optimized layout for on-bridge navigational equipment using a mathematical programming model.

• Journal of Korean Society for Quality Management
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• v.21 no.2
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• pp.17-26
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• 1993

Process fault diagnosis is a complicated matter because quality control problems can result from a variety of causes. These causes include problems with electrical components, mechanical components, human errors, job justification errors, and air conditioning influences. In order to make the system run smoothly with minimum delay, it is necessary to suggest heuristic remedies for the detected faults. Hence, this paper describes a heuristic methodology of fault diagnosis that is performed using statistical patterns generated by quality characteristics The proposed methodology is described briefly as follows: If a sample pattern generated by random variables is similar to the number of prototype patterns, the sample pattern may be matched by any prototype pattern among them to be resembled. This concept is based on the similarity between a sample pattern and the matched prototype pattern. The similarity is calculated as the weighted average of squared deviation, which is expressed as the difference between the relative values of standard normal distribution to be transformed by the observed values of quality characteristics in a sample pattern and the critical values of the corresponding ones in a matched prototype pattern.

• Journal of Korean Society for Quality Management
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• v.30 no.3
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• pp.111-119
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• 2002

Gears are essential elements for mechanical power transmission. Geometric precision is the main factor for characterizing gear grade and qualify. Gear pitch is one of the crucial measurements, which is defined as a distance between two adjacent gear teeth. It is well-known that variability in gear pitches may causes wear-out and vibration noise. Therefore maintaining pitch errors at a low level plays a key role in assuring the gear quality to customers. This paper is concerned with a case study, which presents a computerized system for Inspecting pitch errors in a gear machining process. This system consists of a PC and window-based programs. Although the start and stop is manually accomplished, the process of measuring and analyzing pitch data is automatically conducted in this system. Our purpose lies in reducing inspection cost and time as well as Increasing test reliability. Its operation is briefly illustrated by example. Sometimes a strong autocorrelation is observed from pitch data. We also discuss a process monitoring scheme taking account of autocorrelations.

• Journal of Korean Society for Quality Management
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• v.24 no.4
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• pp.70-89
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• 1996

This paper discusses an optimal burn -in procedure to minimize total costs based on the assumption that some of the components are weak for stress and deteriorate faster than the main components. The procedure will define the costs of burn-in errors. An ideal burn-in consists of process in which all weak (substandard) components and no main (standard) components fail. In practice, the burn-in errors could occur for some reasons. For example, it is impossible to eliminate all weak components through burn-in, due to a nonzero proportion of defectives of the components. Probability model and cost function model are formulated to find the optimal burn-in time that minimizes the expected total cost. Several examples are included to show how to use the results.

• Journal of the Korean Operations Research and Management Science Society
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• v.21 no.1
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• pp.163-170
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• 1996

An errors-in-variables model (EVM) differs from the classical regression model in that in the former the independent variable is also subject to error. This paper shows that to assess the applicability of the ordinary least squares (OLS) estimation procedure to the EVM, the relative dispersion of the independent variable to its error variance must be also considered in addition to Mandel's criterion. The effect of physically reducing the variance of errors in the independent variable on the performance of the OLS slope estimator is also discussed.

• Journal of the Korean Operations Research and Management Science Society
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• v.23 no.4
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• pp.97-109
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• 1998

In this paper, we propose a new approach to solve stochastic fluid flow models applied to the analysis of ceil loss of an ATM multiplexer. Existing stochastic fluid flow models have been analyzed by using linear differential equations. In case of large state space, however. analyzing stochastic fluid flow model without numerical errors is not easy. To avoid this numerical errors and to analyze stochastic fluid flow model with large state space. we develope a new computational algorithm. Instead of solving differential equations directly, this approach uses iterative and numerical method without calculating eigenvalues. eigenvectors and boundary coefficients. As a result, approximate solutions and upper and lower bounds are obtained. This approach can be applied to stochastic fluid flow model having general Markov chain structure as well as to the superposition of heterogeneous ON-OFF sources it can be extended to Markov process having non-exponential sojourn times.

• Management Science and Financial Engineering
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• v.13 no.2
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• pp.141-157
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• 2007

In this paper, we address a design problem and a case study of a K-stage back-light-unit(BLU) inspection system, which is composed of K stages, each of which includes an inspection process and a rework process. Assuming the type I, II errors and the inspection-free policy for items classified as good, we determine the smallest integer of K which can achieve a given target defective rate. If K does not exist, holding the current values of the type I, II errors, we search reversely the defective rate of an assembly line and the defective rate of a rework process, to meet the target defective rate. Our formulae and methodology based on a K-stage inspection system could be applied and extended to similar situations with slight modification.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2011.11a
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• pp.13-15
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• 2011

This report represents analysis of the maritime casualty in terms of Bridge Resource Management. We evaluate the attitudes and knowledge of bridge officer regarding human factors issues that have been identified as causal to mishaps in high-risk situations. So to reduce human errors our goal is to establish effective officer resource management (ORM) program which is based on all subjects for cadets in IMO model course. In harmonization with STCW(The International Convention on Standards of training, Certification and Watch-keeping for Seafarers), as the result, the curriculumss in the maritime education institutions is surveyed to improve our education system and then reduce the human errors by mariners at sea.

• Korean Management Science Review
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• v.19 no.1
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• pp.117-128
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• 2002

In this Paper we investigate the performance of the five efficiency estimation methods which include the stochastic frontier model estimated by maximum likelihood (SFML), the stochastic frontier model estimated by corrected ordinary least squares (SFCOLS), the data envelopment analysis (DIA) model, the combined estimation of SFML and DEA (SFML + DEA), and the combined estimation of SFCOLS arid DIA (SFCOLS+ DEA) using Monte Carlo analysis. The results include: 1) SFML provides most accurate efficiency estimates for the sample sloe 150 or over,2) SFML+DEAor SFCOLS + DIA Perform better for the cases with sample sloe 25, 50, and low random errors, 3) SFCOLS performs better for the close with sample sloe 25, 50, and very high random errors.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1990.04a
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• pp.245-253
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• 1990

In a regression relationship the independent variables are frequently measured with error when measurements are made in the field under less controlled conditions, or when accurate instruments are not available. This paper deals with the prediction problem for the above situation. The integrated mean square error of prediction (IMSE) is developed as a measure of the effect of the errors in the independent variables on the predicted values. The IMSE may be used for assessing the severeness of measurement errors as well as for comparing competing estimators. An example from the area of work measurement is analyzed.